Epidemiological analysis of intramuscular hemorrhage of respiratory and accessory respiratory muscles in fatal drowning cases

The postmortem diagnosis of drowning death and understanding the mechanisms leading to drowning require a comprehensive judgment based on numerous morphological findings in order to determine the pathogenesis and epidemiological characteristics of the findings. Effortful breathing during the drowning process can result in intramuscular hemorrhage in respiratory and accessory respiratory muscles. However, the characteristics of this phenomenon have not been investigated. We analyzed the epidemiological characteristics of 145 cases diagnosed as drowning, in which hemorrhage, not due to trauma, was found in the respiratory muscles and accessory respiratory muscles. Hemorrhage was observed in 31.7% of these cases, and the incidence did not differ by gender or drowning location. The frequency of hemorrhage was significantly higher in months with a mean temperature below 20°C than in months above 20°C, suggesting a relationship between the occurrence of hemorrhage and low environmental temperature. Moreover, the frequency of hemorrhage was significantly higher in the elderly (aged ≥65 years) compared to those <65 years old. In the elderly, the weakening of muscles due to aging may contribute to the susceptibility for intramuscular hemorrhage. Moreover, these intramuscular hemorrhages do not need to be considered in cases of a potential bleeding tendency due to disease such as cirrhosis or medication such as anticoagulants. Our results indicate that intramuscular hemorrhage in respiratory and accessory respiratory muscles can serve as an additional criterion to differentiate between fatal drowning and other causes of death, as long as no cutaneous or subcutaneous hematomas above the muscles with hemorrhages are observed. In addition, the epidemiological features that such intramuscular hemorrhage is more common in cold environments and in the elderly may provide useful information for the differentiation.

Selection of the Optimal Number of Topics for LDA Topic Model—Taking Patent Policy Analysis as an Example

This study constructs a comprehensive index to effectively judge the optimal number of topics in the LDA topic model. Based on the requirements for selecting the number of topics, a comprehensive judgment index of perplexity, isolation, stability, and coincidence is constructed to select the number of topics. This method provides four advantages to selecting the optimal number of topics: (1) good predictive ability, (2) high isolation between topics, (3) no duplicate topics, and (4) repeatability. First, we use three general datasets to compare our proposed method with existing methods, and the results show that the optimal topic number selection method has better selection results. Then, we collected the patent policies of various provinces and cities in China (excluding Hong Kong, Macao, and Taiwan) as datasets. By using the optimal topic number selection method proposed in this study, we can classify patent policies well.

Clinical Significance of a combination of Biochemical Indexes and Immunity Indexes for hepatitis B disease Prediction

.Objectives: To explore the clinical significance of the detection of biochemical indexes and immune indexes in the prediction of hepatitis B (HBV) disease. Methods: 150 patients with HBV disease who were treated in our hospital from 2018 to 2020 were selected and divided into acute HBV group (group A), chronic HBV group (group B) and Cirrhosis group (C group), every group included 50 cases, and 50 healthy people were selected as the control group. Peripheral venous blood was collected from subjects from 4 groups, and immune indexes (plasma immunoglobulin G (IgG), plasma immunoglobulin A (IgA), plasma immunoglobulin M (IgM)) of HBV were measured by immune nephelometry, and biochemical indexes (alanine aminotransferase (ALT) and amino acid transaminase (AST)) of HBV were measured by fasting rate method. Results: Compared with the control group, the immune nephelometry results and fasting rate method showed that the expression of immune indexes (IgG, IgA and IgM) and the expression of biochemical indexes (ALT and AST)in group A, B and C patients were increased significantly (P <0.05), and both of the expression of immune indexes and the biochemical indexes in HBV patients showed an increasing trend accompanied with the aggravation of HBV patients (A<B <C) (P<0.05). Conclusion: The detection of immune indexes and biochemical indexes has important clinical significance in prediction of HBV patients' condition, and detect a combination of biochemical indexes and immune indexes can be used to make a comprehensive judgment to provide a reliable laboratory basis for diagnosis of HBV patients' condition.

Comprehensive Evaluation on Space Information Network Demonstration Platform Based on Tracking and Data Relay Satellite System

Due to the global coverage and real-time access advantages of the Tracking and Data Relay Satellite System (TDRSS), the demonstration platform based on TDRSS can satisfy the new technology verification and demonstration needs of the space information network (evolution from sensorweb). However, the comprehensive evaluation research of this demonstration platform faces many problems: complicated and diverse technical indicators in various areas, coupling redundancy between indicators, difficulty in establishing the number of indicator system layers, and evaluation errors causing by subjective scoring. Concerning the difficulties, this paper gives a method to construct this special index system, and improves the consistency of evaluation results with Analytic Hierarchy Process in Group Decision-Making (AHP-GDM). A comprehensive evaluation index system including five criterions, 11 elements, more than 30 indicators is constructed according to the three-step strategy of initial set classification, hierarchical optimization, and de-redundancy. For the inconsistent scoring of AHP-GDM, a high-speed convergence consistency improvement strategy is proposed in this paper. Moreover, a method for generating a comprehensive judgment matrix (the aggregation of each judgment matrix) aggregation coefficient is provided. Numerical experiments show that this strategy effectively improves the consistency of the comprehensive judgment matrix. Finally, taking the evaluation of TDRSS development as an example, the versatility and feasibility of the new evaluation strategy are demonstrated.

COVID-19 Epidemic: Clinical Characteristics of Patients in Pediatric Isolation Ward

In order to accurately admit children with COVID-19 to an isolation ward, our study retrospectively analyzed the clinical characteristics of children in isolation wards during the COVID-19 epidemic. It was found that 55 cases (83.3%) had fever and 48 cases (72.7%) coughed in the isolated area, 31 cases (47%) had a history of exposure, 26 cases (39.4%) had a decrease in lymphocytes (LYM), more than half had an increase in lactate dehydrogenase and creatine kinase isoenzyme, 14 cases (21.2%) had positive SARS-CoV-2 nucleic acid, 58 cases (87.9%) had abnormal chest computed tomography (CT), and 11 cases (16.7%) had sinus arrhythmia. Therefore, for some suspected children with COVID-19, we can make a comprehensive judgment through clinical symptoms, epidemiological history, LYM number, myocardial enzyme spectrum, chest CT, and electrocardiogram; put these children in an isolation ward for treatment; and then transfer them to a general ward for treatment after excluding COVID-19.

Optimization of Abnormal Point Cloud Recognition in Robot Vision Grinding System Based on Multidimensional Improved Eigenvalue Method (MIEM)

To improve the accurate and sufficient recognition of abnormal points on the workpiece, a multidimensional anomaly point identification approach based on an improved eigenvalue method is proposed in this paper. Whether a point is normal or not depends on the angle between the two adjacent vectors which consisted of four adjacent points around the current focus. The comprehensive judgment is carried out by multidimensional approximation. The numerical simulation and actual experiment validate the efficiency of the proposed method to quickly and accurately identify the abnormal point cloud in the surface point cloud data.

A New System of Face Recognition: Using Fuzziness and Sparsity

In this article, a new human face recognition scheme is proposed. The proposed system is based on the sparsity and fuzziness, and utilizes independent component analysis (ICA). The scheme includes four parts: a fuzzy comprehensive judgment model for estimating whether the information carried by training samples is enough or not, a proper edge extraction operator to discover more hidden information for single image, ICA feature extractor, and a sparse representation model for correlation coefficient calculation to classify testing samples. In view of the intrinsic patterns of gray information distribution of face images, a weighted fuzzy distance for judgement model and cluster analysis is proposed. The new proposed method is tested on ORL, FERET and UMIST databases. The experiment results demonstrate and illustrate the feasibility of the proposed method and the effective performances on recognition rate.